class_docstr: A regular expression-based tokenizer at word boundary.
  This tokenizer default to support MegaMolBART.
  <https://catalog.ngc.nvidia.com/orgs/nvidia/teams/clara/models/megamolbart>
docstr: Saves tokenizer's regex and vocab files
docstr_tok: ["Saves","tokenizer","'s","regex","and","vocab","files"]
code: def save_tokenizer(self, regex_file=None, vocab_file=None):
      """
      Saves tokenizer's regex and vocab files
      """
      regex_file, vocab_file = self._get_regex_vocab_files(
          regex_file=regex_file, vocab_file=vocab_file
      )
  
      logging.info(f"Saving vocabulary to file = {vocab_file}")
      with open(vocab_file, "w") as fp:
          for token in self.vocab:
              fp.write(f"{token[0]}\n")
  
      logging.info(f"Saving regex to file = {regex_file}")
      with open(regex_file, "w") as f:
          f.write(self.regex)
  
imports: import os
  import re
  from typing import Optional
  import pandas
  from nemo.collections.common.tokenizers.char_tokenizer import TokenizerSpec
  from nemo.utils import logging
label_desc: Use image node_id 19 for calling the RegExTokenizer obj's underlying member method code with example usage: obj.save_tokenizer(regex_file, vocab_file) without return types